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Quantitative sonographic imaging of human hard tissue by mathematical modelling of scanning acoustic microscopy data
QUASIM
Prof. Dr. R.Sader
Prof.Dr.M.Grote
Ph.Dr. L.Beilina
Main objectives
• Development of quantitative sonographic imaging by mathematical modelling
• Testing
• Clinical application of ultrasound diagnostics
KSI – Krämer Scientific Instruments GmbH
• Is a private company located in Herborn, Germany• Established in 1990• Provide support and development for the high
technology Scanning Acoustic Microscopy (SAM)• Main directions are research, nondestructive
testing and the process control industry
___________________________________
www.ksi-germany.com
KSI WINSAM 2000Scanning Acoustic Microscope
transmitter receiver
acoustic lens transducer
Coupling fluid
(water)
sample
KSI WINSAM 2000
Production and failure analysis
Repeated information Detailed information
Shows processing and in-service defects
Scan field300 X 300
mmScanning Acoustic Microscope
Mathematical Model ofScanning Acoustic Microscope
transmitter receiver
acoustic lens transducer
Coupling fluid
(water)
sample
G 1
C 0
C(x)
G 2
G 2 G 2
Computational mesh
Computational Algorithm
Initial guessc=c0
Solve forward problem
Solve adjoint problem
Compute gradientand new ch
If gradient > eps
stop
no yes
Adaptive Algorithm
Initial guessc=c0
Solve forward problem on Kh, Tk
Solve adjoint problem on Kh, Tk
Compute gradientand new ch
If gradient decreases
stop
no yes
Initial mesh K0
Initial time partition T0
Residuals > tolrefine elements
Construct new mesh Kh
Construct new time partition Tk
yesno
Solution of the forward problem
c=0.5 inside a spherical inclusion and c=1.0 everywhere else in the domain. Isosurfaces of the computed solution are shown at different times.
Solution of the forward problem
Solution of the forward problem with exact value of the parameter c=0.5 inside a spherical inclusion and c=1.0 everywhere else in the computational domain. We show isosurfaces of the computed solution at different times.
Adaptively refined meshes
Reconstructed parameter
Reconstructed parameter c(x) on different adaptively refined meshes. Isosurfaces of the parameter
field c(x) indicating domains with a given parameter value are shown.
22528 nodes, c =0.66 26133 nodes, c = 0.531 33138 nodes, c=0.51